Antenna Season Report Notebook¶

Josh Dillon, Last Revised January 2022

This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.

In [1]:
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
In [2]:
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
In [3]:
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "102"
csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
In [4]:
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))

Antenna 102 Report

In [5]:
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
In [6]:
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 23 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_
Found 21 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
In [7]:
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'

Load relevant info from summary CSVs¶

In [8]:
this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
            antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
        else:
            antnum = int(row['Ant'])
        if antnum != int(antenna):
            continue
        
        if np.issubdtype(type(row['Node']), np.integer):
            row['Node'] = str(row['Node'])
        if type(row['Node']) == str and row['Node'].isnumeric():
            row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break
In [9]:
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])

Table 1: Per-Night RTP Summary Info For This Atenna¶

This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.

In [10]:
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))

Antenna 102, Node N08:

Out[10]:
JDs A Priori Status Auto Metrics Flags Dead Fraction in Ant Metrics (Jee) Dead Fraction in Ant Metrics (Jnn) Crossed Fraction in Ant Metrics Flag Fraction Before Redcal Flagged By Redcal chi^2 Fraction ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score Average Dead Ant Metric (Jee) Average Dead Ant Metric (Jnn) Average Crossed Ant Metric Median chi^2 Per Antenna (Jee) Median chi^2 Per Antenna (Jnn)
2459838 RF_maintenance 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 6.647630 4.237204 28.873546 29.584371 822.943437 1011.741581 5555.702459 5400.749626 0.6535 0.6176 0.3693 0.000000 0.000000
2459836 RF_maintenance - 100.00% 100.00% 0.00% - - nan nan nan nan nan nan nan nan 0.0385 0.0335 0.0015 nan nan
2459835 RF_maintenance 100.00% 100.00% 100.00% 0.00% - - -1.027986 -0.483611 3.824951 2.462045 1211.366858 1261.228060 4753.209068 6275.748012 0.0351 0.0320 0.0014 nan nan
2459833 RF_maintenance 100.00% 100.00% 100.00% 0.00% - - 9.918974 10.560791 16.785734 17.639875 12507.773553 12947.630869 28769.398329 28593.962102 0.0310 0.0276 0.0014 nan nan
2459832 RF_maintenance 100.00% 0.00% 77.96% 0.00% 100.00% 0.00% 8.945616 9.742282 28.758989 30.997029 539.661111 800.459223 6596.469809 6469.589375 0.7240 0.3852 0.5568 0.000000 0.000000
2459831 RF_maintenance 100.00% 100.00% 100.00% 0.00% - - 0.526564 0.713345 67.259584 71.399685 1637.443951 1649.668249 16474.770130 16530.657947 0.0316 0.0272 0.0014 nan nan
2459830 RF_maintenance 100.00% 0.00% 73.12% 0.00% 100.00% 0.00% 34.261167 34.728754 1.181105 1.063122 723.481767 723.711659 10719.136410 10664.665454 0.7222 0.3921 0.5387 0.000000 0.000000
2459829 RF_maintenance 100.00% 0.00% 0.54% 0.00% 100.00% 0.00% 35.526916 34.909687 3.062913 2.547840 434.131516 431.593267 15833.635311 15727.446451 0.6518 0.5405 0.3763 0.000000 0.000000
2459828 RF_maintenance 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 28.948927 29.458389 1.170627 1.490314 594.623398 591.689291 18545.033189 18446.907174 0.7239 0.4579 0.5024 0.000000 0.000000
2459827 RF_maintenance 100.00% 0.00% 8.06% 0.00% 100.00% 0.00% 25.972982 26.887601 5.136967 3.733902 319.613543 342.559502 4338.347206 4320.349803 0.7136 0.5077 0.4539 0.000000 0.000000
2459826 RF_maintenance 100.00% 0.00% 38.17% 0.00% 100.00% 0.00% 26.611581 27.477988 1.560770 1.779323 711.141044 723.225961 11574.931365 11541.415004 0.7444 0.4280 0.5306 0.000000 0.000000
2459825 RF_maintenance 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 28.677047 29.220513 1.071220 1.407791 390.720172 398.702360 1701.959943 1698.416763 0.7554 0.4961 0.5088 0.000000 0.000000
2459824 RF_maintenance 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 22.252034 21.789416 5.447863 4.796233 492.165915 498.361869 6181.902879 6159.156960 0.6517 0.5635 0.3803 0.000000 0.000000
2459823 RF_maintenance 100.00% 0.00% 10.59% 0.00% 100.00% 0.00% 1.632754 8.471618 14.031290 32.642808 6.692932 13.955530 6.836866 9.101172 0.7191 0.4788 0.4816 48.812566 26.598913
2459822 RF_maintenance 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 3.948624 12.605552 16.612033 30.774484 59.691132 151.588393 84.019952 202.596213 0.7756 0.5112 0.5308 5.220735 3.115356
2459821 RF_maintenance 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 9.285640 12.604521 23.604164 29.832956 89.542334 150.012051 88.665670 144.958587 0.7556 0.5541 0.4841 2.753833 2.339866
2459820 RF_maintenance 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 9.615549 13.835199 15.968190 22.120263 226.849148 344.252717 887.416672 1327.750750 0.6954 0.5718 0.3991 3.310831 2.775775
2459817 RF_maintenance 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 7.287082 5.017442 25.227691 25.189371 50.797792 70.716718 55.857063 69.181909 0.7519 0.6339 0.4733 2.151148 2.140580
2459816 RF_maintenance 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 10.064903 7.087395 24.356219 23.813105 170.558236 169.463978 975.897184 966.411353 0.7391 0.5372 0.5260 2.643713 2.725591
2459815 RF_maintenance 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 7.829338 5.552004 28.092986 28.284872 152.629665 166.212545 1090.108155 1150.229354 0.7396 0.6471 0.4621 2.546013 2.759016
2459814 RF_maintenance 0.00% - - - - - nan nan nan nan nan nan nan nan nan nan nan nan nan
2459813 RF_maintenance 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 17.029072 12.397569 18.656010 17.718039 55.511173 26.688431 63.824472 61.997228 0.1175 0.1016 0.0209 1.147878 1.148878

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

In [11]:
htmls_to_display = []
for am_html in auto_metric_htmls:
    html_to_display = ''
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line:
            htmls_to_display.append(html_to_display)
            break

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.

In [12]:
for i, html_to_display in enumerate(htmls_to_display):
    if i == 100:
        break
    display(HTML(html_to_display))

Antenna 102: 2459838

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
102 N08 RF_maintenance ee Temporal Discontinuties 5555.702459 4.237204 6.647630 29.584371 28.873546 1011.741581 822.943437 5400.749626 5555.702459

Antenna 102: 2459835

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
102 N08 RF_maintenance nn Temporal Discontinuties 6275.748012 -0.483611 -1.027986 2.462045 3.824951 1261.228060 1211.366858 6275.748012 4753.209068

Antenna 102: 2459833

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
102 N08 RF_maintenance ee Temporal Discontinuties 28769.398329 10.560791 9.918974 17.639875 16.785734 12947.630869 12507.773553 28593.962102 28769.398329

Antenna 102: 2459832

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
102 N08 RF_maintenance ee Temporal Discontinuties 6596.469809 8.945616 9.742282 28.758989 30.997029 539.661111 800.459223 6596.469809 6469.589375

Antenna 102: 2459831

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
102 N08 RF_maintenance nn Temporal Discontinuties 16530.657947 0.526564 0.713345 67.259584 71.399685 1637.443951 1649.668249 16474.770130 16530.657947

Antenna 102: 2459830

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
102 N08 RF_maintenance ee Temporal Discontinuties 10719.136410 34.261167 34.728754 1.181105 1.063122 723.481767 723.711659 10719.136410 10664.665454

Antenna 102: 2459829

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
102 N08 RF_maintenance ee Temporal Discontinuties 15833.635311 34.909687 35.526916 2.547840 3.062913 431.593267 434.131516 15727.446451 15833.635311

Antenna 102: 2459828

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
102 N08 RF_maintenance ee Temporal Discontinuties 18545.033189 29.458389 28.948927 1.490314 1.170627 591.689291 594.623398 18446.907174 18545.033189

Antenna 102: 2459827

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
102 N08 RF_maintenance ee Temporal Discontinuties 4338.347206 25.972982 26.887601 5.136967 3.733902 319.613543 342.559502 4338.347206 4320.349803

Antenna 102: 2459826

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
102 N08 RF_maintenance ee Temporal Discontinuties 11574.931365 27.477988 26.611581 1.779323 1.560770 723.225961 711.141044 11541.415004 11574.931365

Antenna 102: 2459825

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
102 N08 RF_maintenance ee Temporal Discontinuties 1701.959943 29.220513 28.677047 1.407791 1.071220 398.702360 390.720172 1698.416763 1701.959943

Antenna 102: 2459824

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
102 N08 RF_maintenance ee Temporal Discontinuties 6181.902879 22.252034 21.789416 5.447863 4.796233 492.165915 498.361869 6181.902879 6159.156960

Antenna 102: 2459823

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
102 N08 RF_maintenance nn Power 32.642808 8.471618 1.632754 32.642808 14.031290 13.955530 6.692932 9.101172 6.836866

Antenna 102: 2459822

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
102 N08 RF_maintenance nn Temporal Discontinuties 202.596213 3.948624 12.605552 16.612033 30.774484 59.691132 151.588393 84.019952 202.596213

Antenna 102: 2459821

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
102 N08 RF_maintenance nn Temporal Variability 150.012051 12.604521 9.285640 29.832956 23.604164 150.012051 89.542334 144.958587 88.665670

Antenna 102: 2459820

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
102 N08 RF_maintenance nn Temporal Discontinuties 1327.750750 9.615549 13.835199 15.968190 22.120263 226.849148 344.252717 887.416672 1327.750750

Antenna 102: 2459817

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
102 N08 RF_maintenance nn Temporal Variability 70.716718 7.287082 5.017442 25.227691 25.189371 50.797792 70.716718 55.857063 69.181909

Antenna 102: 2459816

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
102 N08 RF_maintenance ee Temporal Discontinuties 975.897184 7.087395 10.064903 23.813105 24.356219 169.463978 170.558236 966.411353 975.897184

Antenna 102: 2459815

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
102 N08 RF_maintenance nn Temporal Discontinuties 1150.229354 5.552004 7.829338 28.284872 28.092986 166.212545 152.629665 1150.229354 1090.108155

Antenna 102: 2459814

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
102 N08 RF_maintenance nn Shape nan nan nan nan nan nan nan nan nan

Antenna 102: 2459813

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
102 N08 RF_maintenance ee Temporal Discontinuties 63.824472 12.397569 17.029072 17.718039 18.656010 26.688431 55.511173 61.997228 63.824472
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